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Content related to Best Practices for Enterprise Knowledge Graph Design

How to Prepare Content for AI

Artificial Intelligence (AI) enables organizations to leverage and manage their content in exciting new ways, from chatbots and content summarization to auto-tagging and personalization. Most organizations have a copious amount of content and are looking to use AI to improve … Continue reading

Graph Machine Learning Recommender POC for Public Safety Agency

The Challenge A government agency responsible for regulating and enforcing occupational safety sought to build a content recommender proof-of-concept (POC) that leverages semantic technologies to model the relevant workplace safety domains. The agency aimed to optimize project planning and construction … Continue reading

Measuring the Value of your Semantic Layer: KPIs for Taxonomies, Ontologies, and Knowledge Graphs

Utilizing semantic applications in your business, such as an enterprise taxonomy, ontology, or knowledge graph, can increase efficiency, reduce cognitive load, and improve cohesion across the enterprise, among other benefits. While these benefits are extremely valuable they can be difficult … Continue reading

A Structured Content Model and Multi-Channel Publishing for Rapid Content Distribution

The Challenge EK partnered with the office of a large government agency whose primary mission required them to rapidly distribute real-time updates about current events to government executives and their staff. At the same time, they needed the ability to … Continue reading

Expert Analysis: Top 5 Considerations When Building a Modern Knowledge Portal

Knowledge Portals aggregate and present various types of content – including unstructured content, structured data, and connections to people and enterprise resources. This facilitates the creation of new knowledge and discovery of existing information. The following article highlights five key … Continue reading

The Role of Ontologies with LLMs

In today’s world, the capabilities of artificial intelligence (AI) and large language models (LLMs) have generated widespread excitement. Recent advancements have made natural language use cases, like chatbots and semantic search, more feasible for organizations. However, many people don’t understand … Continue reading